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Purpose: This research paper highlights the economic impact on small and medium-sized enterprises (SMEs) due to Coronavirus outbreaks. It proposes factors that influence the strengthening and survival of SMEs. Design/methodology/approach: In this research, resilience is reflected in the following aspects hope, problem resolution and persistence. This quantitative study analyses a purposive sample of 120 small and medium-sized firms in India. The study's primary data are the responses to questionnaires issued to respondents, analyzed and hypotheses formed and tested using the structural equation modeling (SEM) technique. Findings: The study results show that all the variables significantly reduce the impact of COVID-19 on SMEs. The presented model is expected to help researchers, business modelers, analysts and real professionals with further studies in the SME context. Originality/value: This new approach adds to the business resilience knowledge of SMEs and has practical implications for manufacturing organizations seeking to become robust during and after COVID-19. [ABSTRACT FROM AUTHOR]

Purpose: Supply chain analytics with big data capability are now growing to the next frontier in transforming the supply chain. However, very few studies have identified its different dimensions and overall effects on supply chain performance measures and customer satisfaction. The aim of this paper to design the data-driven supply chain model to evaluate the impact on supply chain performance and customer satisfaction. Design/methodology/approach: This research uses the resource-based view, emerging literature on big data, supply chain performance measures and customer satisfaction theory to develop the big data-driven supply chain (BDDSC) model. The model tested using questionnaire data collected from supply chain managers and supply chain analysts. To prove the research model, the study uses the structural equation modeling technique. Findings: The results of the study identify the supply chain performance measures (integration, innovation, flexibility, efficiency, quality and market performance) and customer satisfaction (cost, flexibility, quality and delivery) positively associated with the BDDSC model. Originality/value: This paper fills the significant gap in the BDDSC on the different dimensions of supply chain performance measures and their impacts on customer satisfaction. [ABSTRACT FROM AUTHOR]

Purpose: Quality 4.0 (Q4.0) is related to quality management in the era of Industry 4.0 (I4.0). In particular, it concentrates on digital techniques used to improve organizational capabilities and ensure the delivery of the best quality products and services to its customer. The aim of this research to examine the vital elements for the Q4.0 implementation. Design/methodology/approach: A review of the literature was carried out to analyze past studies in this emerging research field. Findings: This research identified ten factors that contribute to the successful implementation of Q4.0. The key factors are (1) data, (2) analytics, (3) connectivity, (4) collaboration, (5) development of APP, (6) scalability, (7) compliance, (8) organization culture, (9) leadership and (10) training for Q4.0. Originality/value: As a result of the research, a new understanding of factors of successful implementation of Q4.0 in the digital transformation era can assist firms in developing new ways to implement Q4.0. [ABSTRACT FROM AUTHOR]